Entertainment companies are entering the Age of Data, where they’ll have access to more information than ever about their products, their audiences and how to create, market and distribute one to the other. Now, those companies and their leadership have to be ready to embrace the coming huge opportunities, especially as data-driven competitors such as Netflix, MoviePass and Amazon transform the industry.
That was one message this morning from Stephen F. DeAngelis, CEO and founder of AI provider Enterra Solutions, speaking before a group of Hollywood technology executives in Beverly Hills.
He noted wryly that Hollywood has portrayed AI technologies in dark or at least complicated ways over the years, from the murderous HAL 9000 in 2001: A Space Odyssey to the world-ending SkyNet in the Terminator films to the runaway AIs of Ex Machina and Her.
We’re quite a ways still from AI with that kind of power and autonomy, DeAngelis said, but he cautioned that people think of AI tools in overly limited ways.
“AI has come to mean machine learning,” said DeAngelis, a visiting professional executive in cognitive reasoning platforms at Princeton University’s chemistry department. “There’s nothing particularly intelligent about machine learning.”
By that, he said, machine learning and related technologies are about recognizing patterns in data and anticipating what else might be done with them.
But in the coming era of Intelligent Enterprises, higher-level and more generally capable AI tools will ensure a company “harnesses all the data it has, harmonizes it systematically and is able to make a decision semi-autonomously or autonomously” in most situations. Human managers will review and sign-off mid-level decisions, and reserve most of their focus for high-level strategic decision-making that is framed by the AI tools.
DeAngelis said companies typically spend more than a third of their budgets on marketing of films, TV shows and other products, but could use the tools of high-end artificial intelligence to create disruptive products, distribute those products in new ways and spend their marketing dollars in hyper-targeted and efficient ways.
He trotted out some eye-popping stats: 90 percent of the world’s data has been created in the past two years. The widespread adoption of Internet of Things devices will generate a projected 269 times more data by 2019 than is currently being created.
At the same time, half of all executives say they don’t have ready access to the data they need for informed decision making. Systems need to be created to gather and organize all that data, and then tease out the relevant parts that affect decision-making success.
DeAngelis walked through examples from several other industries that already are using sophisticated AI, including consumer-packaged goods, which he said is relatively similar in its structures to the entertainment industry.
Netflix, for one, is already using AI for program recommendations and, most intriguingly, to generate targeted video “mini-trailers” when you click on a show to consider whether to watch it.
Traditional Hollywood companies haven’t had that relationship with their customers. Too many products have been cut off from direct customer relationships: studios don’t know who bought movie tickets; networks don’t know exactly who’s watching their TV shows; even home-entertainment distributors such as iTunes and Amazon control much of the purchase data.
That situation is changing. MoviePass, for instance, is trying to wrap a data-driven Netflix model around the theatrical movie business. It’s not clear MoviePass can sustain its particular approach, but more restrained business models from theater chains such as AMC and Alamo Drafthouse, among other imitators.
Meanwhile, over-the-top video streaming allows studios the chance to finally build long-term, direct-to-consumer relationships with subscribers that can be a powerful part of the Hollywood of the future. Those opportunities are a big reason why Disney is leaving its deal with Netflix and launching its own subscription VOD service next year.
But DeAngelis said studios already have access to vast reams of data, including Nielsen ratings, ticketing data, social-media posts, demographics, weather, historical box office statistics, and much else.
Pooling that material and feeding it into sophisticated AI tools can help companies better think about everything from what projects they choose to greenlight, to where and when they distribute that project, and even how they deploy marketing resources to drive specific audiences to the resulting show.
“You can make very hyper-personalized recommendations to consumers,” DeAngelis said.
In consumer packaged goods, AI-based tools have allowed companies to uncover unexpected insights, like how promoting one size of a product may appear to lift overall sales but actually may cannibalize purchases of other sizes of the same product.
“Now we look at that data and we’re finding fourth-, fifth-, sixth-order effects behind that data,” DeAngelis said. “Clients didn’t understand the effect of the cannibalization. When you understand what was driving the buying behavior, it allows you to make better decisions.”
In the entertainment world, an apt comparison might be marketing a Star Wars live-action film in a theater versus attracting the same fan base to an animated Star Wars series on Netflix, said Doug Scott, president of Big Block, an Enterra investor.
If a fan stays home to binge on the animated series, is that a loss for the higher-priced film, or were there other reasons why the fan couldn’t get to a theater, so the substitute viewing still represents a win for the studio?
AI tools have allowed CPG companies to spot trends early, such as the rise in sales of kale in concert with a move away from dairy-based products as health-minded people started making smoothies with coconut or soy milk. Those trends emerged by analyzing the entire basket of goods a specific customer or set of customers is purchasing regularly, DeAngelis said.
In entertainment, similar insights might allow development executives to anticipate new kinds of shows and themes before copycats flood the market, a routine headache in Hollywood.
While the opportunities are big to use AI for established brands such as long-running TV shows and film franchises, DeAngelis said they can apply profitably even for small, one-off indie films that don’t have a big marketing budget. That’s particularly true with social media, which tends to be a much richer source of consumer data in entertainment than food.
“In a movie, you have a lot of rich component parts that are probably more detailed than we had in food,” DeAngelis said. “We can drive an effective model against that to optimize the parts.”
Fine-tuning marketing could be a huge opportunity, given that North American businesses spend an average 35 percent of their sales budget there.
“We’re taking that Mad Men art and using data,” DeAngelis said. “It’s supporting scientifically what people had inferred previously. Your product in the market is a complex system. How do we decode it? It’s understanding the underlying causal factors that are really driving the market so you can get lift from your products.”
The next step is to create dashboards that orient slices of the collected data for the specific needs of different parts of an organization, from marketing to distribution to development, and then creating chatbots or intelligent agents that can explain in accessible language what the data insights may be.